Sequential Application of a Cytotoxic Nanoparticle and a PI3K Inhibitor Enhances Antitumor Efficacy
Bibliographic record
Abstract
Nanomedicines that preferentially deploy cytotoxic agents to tumors and molecular targeted therapeutics that inhibit specific aberrant oncogenic drivers are emerging as the new paradigm for the management of cancer. While combination therapies are a mainstay of cancer chemotherapy, few studies have addressed the combination of nanomedicines and molecular targeted therapeutics. Furthermore, limited knowledge exists on the impact of sequencing of such therapeutics and nanomedicines on the antitumor outcome. Here, we engineered a supramolecular cis-platinum nanoparticle, which induced apoptosis in breast cancer cells but also elicited prosurvival signaling via an EGF receptor/phosphoinositide 3-kinase (PI3K) pathway. A combination of mathematical modeling and in vitro and in vivo validation using a pharmacologic inhibitor of PI3K, PI828, demonstrate that administration of PI828 following treatment with the supramolecular cis-platinum nanoparticle results in enhanced antitumor efficacy in breast cancer as compared with when the sequence is reversed or when the two treatments are administered simultaneously. This study addresses, for the first time, the impact of drug sequencing in the case of a combination of a nanomedicine and a targeted therapeutic. Furthermore, our results indicate that a rational combination of cis-platinum nanoparticles and a PI3K-targeted therapeutic can emerge as a potential therapy for breast cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".